【 中文摘要 】本发明公开了一种面向领域数据的语义检索方法，利用本体来描述某个领域的语义信息，使得计算机更准确得理解用户查询内容，进而实现语义层面的检索，在分析现有技术的基础上，结合语义网本体的结构特点，提出了一种面向领域数据的语义索引模型，模型根据关键词在本体中的位置推断关键词与不同实例之间的语义相关度，将相关度权重写入关键词对应的实例倒排列表，降低了语义检索时相似度计算的复杂度，提高了检索的效率。本发明所述方法将检索从关键字简单匹配的语法层次提高到计算机可以理解的语义层次，使计算机能够读懂输入的关键词，从而实现了检索的智能化。

【 英文摘要 】The invention discloses a semantic retrieval method oriented to field data. Semantic information of a certain field is described by using a body, so that a computer understands content inquired by a user more accurately, and retrieval on a semantic level is realized. A semantic retrieval model oriented to field data is provided in combination with the structural characteristics of a semantic network body on the basis of analyzing the prior art. The semantic relativity between a keyword and different examples is deduced by using the model according to the position of the keyword in the body, and a relativity weight is written into an example inverted list which corresponds to the keyword, so that the similarity computation complexity during semantic retrieval is lowered, and the retrieval efficiency is increased. According to the method disclosed by the invention, retrieval is raised from a grammatical level of simple keyword matching to a semantic level understandable for the computer, and the computer can understand the input keyword, so that retrieval intelligence is realized.

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